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MEDIUM severity

CVE-2022-23572 — tensorflow

MEDIUMFix: tensorflow/tensorflow@cb16478

CVE-2022-23572 is a medium-severity (CVSS 6.5) CWE-754 vulnerability in tensorflow. 1 public exploit reference exists, so weaponization risk is real. A fix is available for tensorflow — see the affected versions and patch details below.

Crash when type cannot be specialized in Tensorflow

Also known asBIT-tensorflow-2022-23572GHSA-rww7-2gpw-fv6jPYSEC-2022-136PYSEC-2022-81PYSEC-2026-3241
Published
Updated
Affected
9 pkgs
Patched
9 / 9
Exploits
1 known
Exploitation data as of Oct 8, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

  • CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.

Exploitation and automatability from CISA’s SSVC triage for CVE-2022-23572.

EPSS Exploitation Probability

via FIRST.org ↗
1.0%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs62th percentile — riskier than 62% of all scored CVEsHighest risk
0.01%0.50%1.00%1.50%0.5%1.0%Apr 26Aug 26Oct 26

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

CVE-2022-23572 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.

Where this sits among everything scored

Of 385,987 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.

Real-World Exposure

9 pkgs affected
🐍tensorflow🐍tensorflow🐍tensorflow🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-cpu🐍tensorflow-gpu🐍tensorflow-gpu+1 more

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

Under certain scenarios, TensorFlow can fail to specialize a type during shape inference:

void InferenceContext::PreInputInit(
    const OpDef& op_def, const std::vector<const Tensor*>& input_tensors,
    const std::vector<ShapeHandle>& input_tensors_as_shapes) {
  const auto ret = full_type::SpecializeType(attrs_, op_def);
  DCHECK(ret.status().ok()) << "while instantiating types: " << ret.status();
  ret_types_ = ret.ValueOrDie();
  // ... 
}

However, DCHECK is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the ValueOrDie line. This results in an assertion failure as ret contains an error Status, not a value. In the second case we also get a crash due to the assertion failure.

Patches

We have patched the issue in GitHub commit cb164786dc891ea11d3a900e90367c339305dc7b.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Affected Packages

9 total 9 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.5.3pip install --upgrade 'tensorflow==2.5.3'
🐍PyPItensorflow≥ 2.6.0&&< 2.6.32.6.3pip install --upgrade 'tensorflow==2.6.3'
🐍PyPItensorflow≥ 2.7.0&&< 2.7.12.7.1pip install --upgrade 'tensorflow==2.7.1'
🐍PyPItensorflow-cpuall versions2.5.3pip install --upgrade 'tensorflow-cpu==2.5.3'
🐍PyPItensorflow-cpu≥ 2.6.0&&< 2.6.32.6.3pip install --upgrade 'tensorflow-cpu==2.6.3'
🐍PyPItensorflow-cpu≥ 2.7.0&&< 2.7.12.7.1pip install --upgrade 'tensorflow-cpu==2.7.1'

Affected Products

1 product · 3 configurations
Application
tensorflowgoogle
≥ 2.6.0 && ≤ 2.6.2
1 version
2.7.0
Exploits & PoCs
1

Research use only. For defensive security, authorized penetration testing, and academic research only. Never execute exploit code against systems without explicit written authorization.

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update tensorflow to 2.5.3 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2022-23572 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Frequently Asked Questions

### Impact Under certain scenarios, TensorFlow can fail to specialize a type during [shape inference](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174): ```cc void InferenceContext::PreInputInit( const OpDef& op_def, const std::vector<const Tensor*>& input_tensors, const std::vector<ShapeHandle>& input_tensors_as_shapes) { const auto ret = full_type::SpecializeType(attrs_, op_def); DCHECK(ret.status().ok()) << "while instantiating types: " << ret.status(); ret_types_ = ret.ValueOrDie();
O3 Security · Impact-Aware SCA

Is CVE-2022-23572 in your dependencies?

Find it across PyPI, including transitive dependencies.

CVE-2022-23572: tensorflow — Fixed in 2.5.3